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Statistics and Data Analysis for Financial Engineering (Springer Texts in Statistics)

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Financial engineers have access to enormous quantities of data but need powerful methods for extracting quantitative information, particularly about volatility and risks. Key features of this textbook are: illustration of concepts with financial markets and economic data, R Labs with real-data exercises, and integration of graphical and analytic methods for modeling and diagnosing modeling errors. Despite some overlap with the author's undergraduate textbook Statistics and Finance: An Introduction, this book differs from that earlier volume in several important aspects: it is graduate-level; computations and graphics are done in R; and many advanced topics are covered, for example, multivariate distributions, copulas, Bayesian computations, VaR and expected shortfall, and cointegration.

The prerequisites are basic statistics and probability, matrices and linear algebra, and calculus.

Some exposure to finance is helpful.

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Partial Differential Equations: Vol. 1 Foundations and Integral Representations (Universitext)
Partial Differential Equations: Vol. 1 Foundations and Integral Representations (Universitext)
From the reviews:

"Friedrich Sauvigny's remarkable two-volume opus constitutes the author's attempt to treat the beautiful and difficult subject of PDEs in a thorough and instructive way. is a fine place to learn PDEs with the goal of doing serious work in the field. Friedrich Sauvigny's scholarship is exemplary and thorough; at the same...

Linear Algebra and Geometry
Linear Algebra and Geometry

This book is the result of a series of lectures on linear algebra and the geometry of multidimensional spaces given in the 1950s through 1970s by Igor R. Shafarevich at the Faculty of Mechanics and Mathematics of Moscow State University.

Notes for some of these lectures were preserved in the faculty library, and these were used...
Numerical Methods in Finance with C++ (Mastering Mathematical Finance)
Numerical Methods in Finance with C++ (Mastering Mathematical Finance)

Driven by concrete computational problems in quantitative finance, this book provides aspiring quant developers with the numerical techniques and programming skills they need. The authors start from scratch, so the reader does not need any previous experience of C++. Beginning with straightforward option pricing on binomial trees, the book...


Partial Differential Equations 2: Functional Analytic Methods (Universitext)
Partial Differential Equations 2: Functional Analytic Methods (Universitext)
This comprehensive two-volume textbook presents the whole area of Partial Differential Equations - of the elliptic, parabolic, and hyperbolic type - in two and several variables. Special emphasis is put on the connection of PDEs and complex variable methods.

In this second volume the following topics are treated: Solvability of...

Introduction to Differential Calculus: Systematic Studies with Engineering Applications for Beginners
Introduction to Differential Calculus: Systematic Studies with Engineering Applications for Beginners

Enables readers to apply the fundamentals of differential calculus to solve real-life problems in engineering and the physical sciences

Introduction to Differential Calculus fully engages readers by presenting the fundamental theories and methods of differential calculus and then showcasing how the discussed concepts can be...

Solving Nonlinear Partial Differential Equations with Maple and Mathematica
Solving Nonlinear Partial Differential Equations with Maple and Mathematica

The emphasis of the book is given in how to construct different types of solutions (exact, approximate analytical, numerical, graphical) of numerous nonlinear PDEs correctly, easily, and quickly. The reader can learn a wide variety of techniques and solve numerous nonlinear PDEs included and many other differential equations, simplifying...

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